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Researchers at the University of Oregon are taking a biology-inspired approach to creating bionic eyes that could change the trajectory of eye implants. ....
The industrial Internet of Things (IIoTs) network life is shortened due to sensor node (SN) energy limitations and computational capability. As a result, optimum node location estimation and efficient energy usage are two critical IIoT requirements. This work reduces energy consumption by performing node localization and cluster-based routing using an improved evolutionary algorithm called Cat Swarm Optimization (CSO). First, the CSO method is used to optimize the bio-inspired node's location. Second, to conserve SN energy in the IIoT network, a cluster-based routing technique is used. The objective function is defined as minimizing the average distance between the cluster and its SNs while selecting the most energy-efficient Cluster Head (CH). In terms of fitness value, the Improved CSO (ICSO) algorithm outperforms the Particle Swarm Optimization (PSO) algorithm. In this paper, real-time test-bed analysis was used to investigate the performance of both node localization and energ ....
Buildings, bridges and offshore infrastructure might one day stand on pilings modeled on snakeskin, based on research at the University of California, Davis, Department of Civil and Environmental Engineering. With surfaces designed to move through soil more easily in one direction than the other, snakeskin pilings would be easier to drive into soil but difficult to pull out. ....